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Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is co...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836900/ https://www.ncbi.nlm.nih.gov/pubmed/33520118 http://dx.doi.org/10.1016/j.csbj.2020.12.010 |
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author | Liu, Hui Lin, Shujin Ao, Xiulan Gong, Xiangwen Liu, Chunyun Xu, Dechang Huang, Yumei Liu, Zhiqiang Zhao, Bixing Liu, Xiaolong Han, Xiao Ye, Hanhui |
author_facet | Liu, Hui Lin, Shujin Ao, Xiulan Gong, Xiangwen Liu, Chunyun Xu, Dechang Huang, Yumei Liu, Zhiqiang Zhao, Bixing Liu, Xiaolong Han, Xiao Ye, Hanhui |
author_sort | Liu, Hui |
collection | PubMed |
description | In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases. |
format | Online Article Text |
id | pubmed-7836900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-78369002021-01-26 Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 Liu, Hui Lin, Shujin Ao, Xiulan Gong, Xiangwen Liu, Chunyun Xu, Dechang Huang, Yumei Liu, Zhiqiang Zhao, Bixing Liu, Xiaolong Han, Xiao Ye, Hanhui Comput Struct Biotechnol J Research Article In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases. Research Network of Computational and Structural Biotechnology 2020-12-24 /pmc/articles/PMC7836900/ /pubmed/33520118 http://dx.doi.org/10.1016/j.csbj.2020.12.010 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Liu, Hui Lin, Shujin Ao, Xiulan Gong, Xiangwen Liu, Chunyun Xu, Dechang Huang, Yumei Liu, Zhiqiang Zhao, Bixing Liu, Xiaolong Han, Xiao Ye, Hanhui Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 |
title | Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 |
title_full | Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 |
title_fullStr | Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 |
title_full_unstemmed | Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 |
title_short | Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 |
title_sort | meta-analysis of transcriptome datasets: an alternative method to study il-6 regulation in coronavirus disease 2019 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836900/ https://www.ncbi.nlm.nih.gov/pubmed/33520118 http://dx.doi.org/10.1016/j.csbj.2020.12.010 |
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